Background Early identification of neurodevelopmental conditions during the pre-school years (ages 3–6) is critical for timely intervention, yet traditional questionnaire-based screeners suffer from low positive predictive value, late detection, and inequitable access. Artificial intelligence (AI) and machine-learning...
A. Arslan, F. Gül· Frontiers in Psychology· 0 citations
This paper compares five activation functions on MNIST and Fashion-MNIST using an idealized software configuration and a hardware configuration parameterized by the measured conductance characteristics of a fabricated TiO 2 device, and inverts the one familiar from digital deep learning.
Baki Gökgöz, Tolga Aydın, F. Gül· Scientific Reports· 0 citations
An interpretable machine learning workflow is developed that predicts both the total dielectric constant and the HSE bandgap of polymer repeat units directly from a monomer structure, using an open density-functional-theory dataset of 284 four-block polymers.
The combined experimental and computational findings provide mechanistic insights into P. scoparius activity and support its relevance within the context of natural product-based cancer therapy, highlighting its potential for further preclinical development.
S. Chabane, A. Boudjelal, L. Pulvirenti et al.· Molecules· 0 citations
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